Localization and tracking for simultaneous speakers based on time-frequency method and Probability Hypothesis Density filter
Quang H. Nguyen, JongSuk Choi · 2011
In this paper we present the two steps system of localization and tracking to work in context of simultaneous speakers. The localization algorithm is based on time-frequency method which uses an array of three microphones and it enables to locate multiple sound sources in a single time-frame. Localization results with missing detection and clutter are post-processed by the Probability Hypothesis Density (PHD) filter - based tracking algorithm to estimate the smoothed trajectory of each speaker. The experiments carried out on real data recording show that our method outperforms the multi-target particle filter (MTPF) - based algorithm and is effective in practical application of human-robot interaction.